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This document provides a review of various data mining techniques used for online transaction fraud detection. It begins by classifying different types of financial frauds and data mining approaches. Some key data mining techniques discussed for fraud detection include neural networks, decision trees, clustering, outlier detection and prediction models. Issues around sparse fraud data and improving accuracy of fraud detection systems are also addressed. A hybrid approach combining data mining at both the da
- Author
- Selva Raj
- Language
- EN